The ACIA assessment process

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Published: February 9, 2010, 2:43 pm
Updated: May 7, 2012, 5:59 pm
Author: International Arctic Science Committee
Topic Editor: Peter Saundry
Topics:

This is Section 1.4 of the Arctic Climate Impact Assessment
Authors: Henry Huntington, Gunter Weller. Contributing Authors: Elizabeth Bush,Terry V. Callaghan,Vladimir M. Kattsov, Mark Nuttall

The nature of science assessment (1.4.1)

The ACIA is a “science assessment” in the tradition of other major international assessments of current environmental issues. For example, the IPCC, the international body mandated to assess the relevant information for understanding the risk of human-induced climate change, recently released its Third Assessment Report[1]. The WMO and UNEP jointly released their latest assessments of the issue of stratospheric ozone depletion[2].Two Arctic Council working groups, AMAP and CAFF, have also recently completed science assessments of, respectively, pollution and biodiversity in the circumpolar Arctic[3]. All of these, and indeed all other assessments, have in common the purpose of providing scientific advice to decision makers who need to develop strategies regarding their respective areas of responsibility.The ACIA responds directly to the request of the Arctic Council for an assessment that can provide the scientific basis for policies and actions.

The essence of a science assessment is to analyze critically and judge definitively the state of understanding on an issue that is inherently scientific in nature. It is a point-in- time evaluation of the existing knowledge base, highlighting both areas of confidence and consensus and areas of uncertainty and disagreement in the science. Another aim of an assessment is to stimulate research into filling emerging knowledge gaps and solving unresolved issues. A science assessment thus draws primarily on the available literature, rather than on new research.To be used within an assessment, a study must have been published according to standards of scientific excellence. (With regard to the incorporation of indigenous knowledge, see the discussion in section 1.4.3.) Publications in the open, peer-reviewed scientific literature meet this standard. Other resources, such as technical publications by government agencies, may be included if they have undergone review and are publicly available.

Concepts and tools in climate assessment (1.4.2)

The arctic climate system is complex.The processes of climate and the ways in which various phenomena affect one another – the feedbacks in the system – are still not fully understood. Specific feedbacks are introduced by the cryosphere and, in particular, by sea ice with its complex dynamics and thermodynamics. Other complex features include the internal dynamics of the polar atmosphere, stratification of both the lower troposphere and the ocean, and phenomena such as the dryness of the air and multiple cloud layers. All these add to the challenge of developing effective three-dimensional models and constructing climate scenarios based on the outcome of such models[4].

“Climate scenario” means a plausible representation of the future climate that is consistent with assumptions about future emissions of greenhouse gases and other pollutants (emissions scenarios) and with the current understanding of the effects that increased atmospheric concentrations of these components have on climate[5]. Correspondingly, a “climate change scenario” is the difference between conditions under a future climate scenario and those of today’s climate. Being dependent on a number of assumptions about future human activities and their impact on the composition of the atmosphere, climate and climate change scenarios are not predictions, but plausible descriptions of possible future climates.

Selection of climate scenarios for impact assessments is always controversial and vulnerable to criticism[6]. The following criteria are suggested[7] for climate scenarios to be most useful to impact assessors and policy makers: (1) consistency with global warming projections over the period 1990 to 2100 ranging from 1.4 to 5.8 ºC[8]; (2) physical plausibility; (3) applicability in impact assessments, providing a sufficient number of variables across relevant temporal and spatial scales; (4) representativeness, reflecting the potential range of future regional climate change; and (5) accessibility. It is preferable for impact researchers to use several climate scenarios, generated by different models where possible, in order to evaluate a greater range of possible futures. Practical limitations, however, typically mean researchers can only work with a small number of climate scenarios.

One starting point for developing a climate change scenario is to select an emissions scenario, which provides a plausible projection of future emissions of substances such as greenhouse gases and aerosols.The most recent IPCC emissions scenarios used in model simulations are those published in the Special Report on Emissions Scenarios[9].The SRES emissions scenarios were built around four basic paths of development that the world may take in the 21st century. It should be noted that no probabilities were assigned to the various SRES emissions scenarios.

During the initial stage of the ACIA process, to stay coordinated with current IPCC efforts, it was agreed that the ACIA should work from IPCC SRES emissions scenarios[10]. At that time, most of the available or soon-to-be-available simulations that allowed their own uncertainties to be assessed used the A2 and B2 emissions scenarios[11]:

  • The A2 emissions scenario assumes an emphasis on economic development rather than conservation. Population is projected to increase continuously.
  • The B2 emissions scenario differs in having a greater emphasis on environmental concerns than economic concerns. It has intermediate levels of economic growth and a population that, although continuously increasing, grows at a slower rate than that in the A2 emissions scenario.

Both A2 and B2 can be considered intermediate scenarios. For reasons of schedule and limitations of data storage, ACIA had to choose one as the central emissions scenario. B2 was chosen because at the time it had been more widely used to generate scenarios, with A2 as a plausible alternative as its use increased.

Once an emissions scenario is selected, it must be used in a climate model (atmosphere–ocean general circulation model, or AOGCM; those used in this assessment are coupled atmosphere-land-ice-ocean models) to produce a climate scenario. Considering the large and increasing number of models available, selecting the models and model outputs for the assessment was not a trivial matter.The IPCC[12] concluded that no single model can be considered “best” and that it is important to utilize results from a range of coupled models.

Initially, a set of the most recent and comprehensive AOGCMs whose outputs were available from the IPCC Data Distribution Centre were chosen. Later, this set was reduced to five AOGCMs (two European and three North-American) for practical reasons. The treatment of land surfaces and sea ice is included in all these models, but with varying degrees of complexity. The five ACIA-designated models and the institutes that run them are:

  • CGCM2 (Canadian Centre for Climate Modelling and Analysis)
  • CSM_1.4 (National Center for Atmospheric Research, USA)
  • ECHAM4/OPYC3 (Max-Planck Institute for Meteorology, Germany)
  • GFDL-R30_c (Geophysical Fluid Dynamics Laboratory, USA)
  • HadCM3 (Hadley Centre for Climate Prediction and Research, UK).

In the initial phase of the ACIA, at least one simulation using the B2 emissions scenario and extending to 2100 was accomplished with each of the five ACIA-designated models. For climate change scenarios, the ACIA climate baseline is 1981–2000. Any differences from the more familiar IPCC baseline of 1961–1990 were small.Three 20-year time slices are the foci of the ACIA for the 21st century: 2011–2030, 2041–2060, and 2071–2090, corresponding to near-term, mid-term, and longer-term outlooks for climate change.A complete description and discussion of the modeling work under ACIA, as well as its limitations, are provided in Chapter 4.

Other types of scenario were also used by chapter authors or by the studies on which the chapters of the assessment are based. These include analogue scenarios of a future climate, based on past (instrumentally recorded) or paleo (geologically recorded) warm climates (i.e., temporal analogue scenarios) or current climates in warmer regions (i.e., spatial analogue scenarios). Although instrumental records provide relatively poor coverage for most of the Arctic, their use avoids uncertainties associated with interpreting other indicators, providing a significant advantage over other approaches. Overall, analogue scenarios were used widely in the ACIA, supplementing the scenarios produced by numerical models. No single impact model was used in the impacts chapters of the assessment; each chapter made use of its own approaches. Further work in this area might consider the need and ability to develop impact models that can be used to address the diversity of topics addressed in this assessment. Another need is for models and scenarios that are able to show more detailed regional and sub-regional variations and that can be used for local impact assessments.

Approaches for assessing impacts of climate and UV radiation (1.4.3)

The study of climate and UV radiation involves detailed measurements of physical parameters and the subsequent analysis of results to detect patterns and trends and to create quantitative models of these trends and their interactions. As Chapters 2, 4, 5, and 6 show, this is not a trivial undertaking. The next step, using measurements and models to assess the likely impacts of changes in climate and UV radiation, is even more complex and uncertain. Ecosystems and societies are changing in ways great and small and are driven by many cooccurring factors regardless of variability in climate and UV radiation. Determining how changes in climate and UV radiation may affect dynamic systems relies on several sources of data and several approaches to analysis (see further discussion in Chapter 7).

Most experimental and empirical data can reveal how climate and UV radiation affect plants, animals, and human communities. Observational studies and monitoring can document changes in climate and UV radiation over time together with associated changes in the physical, biological, and social environment.The drawback to observational studies is that they are opportunistic and require that the correct parameters are tracked in a system in which change actually occurs. Establishing causal connections is harder, but can be done through studies of the physical and ecological processes that link environmental components. Experimental studies involve manipulations of small components of the environment, such as vegetation plots or streams. In these cases, the researcher determines the simulated climate or UV radiation change or changes, so there is great control over the conditions being studied.The drawback is that the range of climate and UV radiation conditions may not match that anticipated by various scenarios used for regional assessments, limiting the applicability of the experimental data to the assumptions of the particular assessment.

The use of analogues, as described at the end of the previous section, can help identify potential consequences of climate change. Looking at past climates and climate change events can help identify characteristic biota and how they change. Spatial analogues can be used to compare ecosystems that exist now with the ecosystems where similar climate conditions are anticipated in the future.A strength of analogues is that they enable an examination of actual changes over an ecosystem, rather than hypothetical changes or changes to small experimental sites.Their weakness is that perfect analogues cannot be found, making interpretation difficult because of the variety of factors that cannot be controlled.

For assessing impacts on societies, a variety of social and economic models and approaches can be used. Examining resilience, adaptation, and vulnerability (see further discussion in Chapter 17) offers a powerful means of understanding at least some of the dynamics and complexity associated with human responses to environmental and other changes. As with changes to the natural environment, examining societal dynamics can be achieved through models, observations, and the use of analogues.

These scientific approaches can be complemented by another source of information; indigenous and local knowledge1.This assessment makes use of such knowledge to an unprecedented degree in an exercise of this kind. Some extra attention to the topic is therefore warranted here. Indigenous residents of the Arctic have for millennia relied on their knowledge of the environment in order to provide food and other materials and to survive its harsh conditions. More recent arrivals, too, may have a wealth of local knowledge about their area and its environment.The high interannual variability in the Arctic has forced its residents to be adaptable to a range of conditions in climate and the abundance and distribution of animals. Although indigenous and local knowledge is not typically gathered for the specific purpose of documenting climate and UV radiation changes, it is nonetheless a valuable source of insight into environmental change over long periods and in great local detail, often covering areas and seasons in which little scientific research has been conducted.The review of documented information by the communities concerned is a crucial step in establishing whether the information contained in reports about indigenous and local knowledge reliably reflects community perspectives.This step of community review offers a similar degree of confidence to that provided by the peer-review process for scientific literature.

Determining how best to use indigenous knowledge in environmental assessments, including assessments of the impacts of climate and UV radiation, is a matter of debate[13], but the quality of information generated in careful studies has been established for many aspects of environmental research and management[14]. In making use of indigenous knowledge, several of its characteristics should be kept in mind. It is typically qualitative rather than quantitative, does not explicitly address uncertainty, and is more likely to be based on observations over a long period than on comparisons of observations taken at the same time in different locations.

Note: Many terms are used to refer to the type of knowledge referred to in this assessment as “indigenous knowledge”. Among the terms in use in the literature are traditional knowledge, traditional ecological knowledge, local knowledge (often applied to the knowledge of non-indigenous persons), traditional knowledge and wisdom, and a variety of specific terms for different peoples, such as Saami knowledge or Inuit Qaujimajatuqangit. Within the context of this assessment, “indigenous knowledge” should be taken broadly, to include observations, interpretations, concerns, and responses of indigenous peoples. For further discussion see Chapter 3.

Identifying mechanisms of change can be particularly difficult. It is also important to note that indigenous knowledge refers to the variety of knowledge systems in the various cultures of the Arctic and is not merely another discipline or method for studying arctic climate.

Using more than one approach wherever possible can reduce the uncertainties inherent in each of these approaches.The ACIA has drawn on all available information, noting the limitations of each source, to compile a comprehensive picture of climate change and its impacts in the Arctic. Existing climate models project a wide range of conditions in future decades. Not all have been or can be studied empirically, nor can field studies examine enough sites to be fully representative of the range of changes across the Arctic. Instead, using data from existing studies to assess impacts from regional scenarios and models requires some extrapolation and judgment. In this assessment, the chapters addressing impacts may not be able to assess the precise conditions projected in the scenarios upon which the overall assessment is based. Instead, where necessary they will describe what is known and examine how that knowledge relates to the conditions anticipated by the scenarios.

Chapter 1: Introduction to the ACIA (The ACIA assessment process)

1.1 An Introduction to the Arctic Climate Impact Assessment
1.2. Why assess the impacts of changes in climate and UV radiation in the Arctic?
1.3. The Arctic Climate Impact Assessment
1.4. The assessment process
1.5. The Arctic: geography, climate, ecology, and people
1.6. An outline of the assessment

References

Citation

Committee, I. (2012). The ACIA assessment process. Retrieved from http://editors.eol.org/eoearth/wiki/The_ACIA_assessment_process
  1. ↑ IPCC, 2001a. Climate Change 2001:The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. J.T. Houghton,Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, K. Maskell and C.A. Johnson (eds.). Cambridge University Press, 881pp.IPCC, 2001b. Climate Change 2001: Impacts, Adaptation, and Vulnerability. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. J.J. McCarthy, O.F. Canziani, N.A. Leary, D.J. Dokken and K.S.White (eds.). Cambridge University Press, 1032pp.
  2. ↑ WMO, 2003. Scientific Assessment of Ozone Depletion: 2002. Global Ozone Research and Monitoring Project – Report No. 47,World Meteorological Organization, Geneva.UNEP, 2003. Environmental Effects of Ozone Depletion and its Interactions with Climate Change: 2002 Assessment. United Nations Environment Programme. Journal of Photochemical and Photobiological Sciences, Special issue. DOI: 10.1039/b211913g.
  3. ↑ AMAP, 2002. Arctic Pollution 2002. Arctic Monitoring and Assessment Programme, Oslo, xi + 111pp.AMAP, 2003a. AMAP Assessment 2002: Human Health in the Arctic. Arctic Monitoring and Assesment Programme, Oslo, xiii + 137pp.AMAP, 2003b. AMAP Assessment 2002:The Influence of Global Change on Contaminant Pathways to, within, and from the Arctic. Arctic Monitoring and Assessment Programme, Oslo, xi + 65pp.AMAP, 2004a. AMAP Assessment 2002: Persistent Organic Pollutants (POPs) in the Arctic. Arctic Monitoring and Assessment Programme, Oslo, xvi+310pp.AMAP, 2004b. AMAP Assessment 2002: Radioactivity in the Arctic. Arctic Monitoring and Assessment Programme, Oslo, xi + 100pp.AMAP, 2004c. AMAP Assessment 2002: Heavy Metals in the Arctic. Arctic Monitoring and Assessment Programme, Oslo.CAFF, 2001. Arctic Flora and Fauna: Status and Conservation. Conservation of Arctic Flora and Fauna, Edita, Helsinki, 272pp.
  4. ↑ Randall, D., J. Curry, D. Battisti, G. Flato, R. Grumbine, S. Hakkinen, D. Martinson, R. Preller, J.Walsh and J.Weatherly, 1998. Status of and outlook for large-scale modeling of atmosphere-ice-ocean interactions in the Arctic. Bulletin of the American Meteorological Society, 79:197–219.Stocker,T.F., G.K.C. Clarke, H. Le Treut, R.S. Lindzen,V.P. Meleshko, R.K. Mugara,T.N. Palmer, R.T. Pierrehumbert, P.J. Sellers, K.E. Trenberth and J.Willebrand, 2001. Physical climate processes and feedbacks. In: J.T. Houghton,Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, K. Maskell and C.A. Johnson (eds.). Climate Change 2001:The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change, pp. 417–470. Cambridge University Press.
  5. ↑ IPCC-TGCIA, 1999. Guidelines on the Use of Scenario Data for Climate Impact and Adaptation Assessment.Version 1. Prepared by T.R. Carter, M. Hulme and M. Lal, Intergovernmental Panel on Climate Change,Task Group on Scenarios for Climate Impact Assessment, 69pp.
  6. ↑ Smith, J.B., M. Hulme, J. Jaagus, S. Keevallik, A. Mekonnen and K. Hailemariam, 1998. Climate Change Scenarios. In: J.F. Feenstra, I. Burton, J. Smith and R.S.J.Tol (eds.). Handbook on Methods for Climate Change Impact Assessment and Adaptation Strategies, Version 2.0, pp. 3-1 - 3-40. United Nations Environment Programme and Institute for Environmental Studies,Vrije Universiteit, Amsterdam.
  7. ↑ Mearns, L.O., M. Hulme,T.R. Carter, R. Leemans, M. Lal and P. Whetton, 2001. Climate Scenario Development. In: J.T. Houghton, Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, K. Maskell and C.A. Johnson (eds.). Climate Change 2001: The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change, pp. 739–768. Cambridge University Press.
  8. ↑ IPCC, 2001a. Climate Change 2001:The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. J.T. Houghton,Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, K. Maskell and C.A. Johnson (eds.). Cambridge University Press, 881pp.
  9. ↑ Naki5enovi5, N., J. Alcamo, G. Davis, B. de Vries, J. Fenhann, S. Gaffin, K. Gregory, A. Grübler,T.Y. Jung,T. Kram, E.L. La Rovere, L. Michaelis, S. Mori,T. Morita,W. Pepper, H. Pitcher, L. Price, K. Raihi, A. Roehrl, H.-H. Rogner, A. Sankovski, M. Schlesinger, P. Shukla, S. Smith, R. Swart, S. van Rooijen, N.Victor and Z. Dadi, 2000. IPCC Special Report on Emissions Scenarios. Cambridge University Press, 599pp.
  10. ↑ Källén, E.,V. Kattsov, J.Walsh and E.Weatherhead, 2001. Report from the Arctic Climate Impact Assessment Modeling and Scenarios Workshop. Stockholm, 29–31 January 2001, 35pp.
  11. ↑ Cubasch, U., G.A. Meehl, G.J. Boer, R.J. Stouffer, M. Dix, A. Noda, C.A. Senior, S. Raper and K.S.Yap, 2001. Projections of future climate change. In: J.T. Houghton,Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, K. Maskell and C.A. Johnson (eds.). Climate Change 2001: The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change, pp. 525–582. Cambridge University Press.
  12. ↑ McAvaney, B.J., C. Covey, S. Joussaume,V. Kattsov, A. Kitoh, W. Ogana, A.J. Pitman, A.J.Weaver, R.A.Wood and Z.-C. Zhao, 2001. Model evaluation. In: J.T. Houghton,Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, K. Maskell and C.A. Johnson (eds.). Climate Change 2001:The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change, pp. 471–524. Cambridge University Press.
  13. ↑ Howard, A. and F.Widdowson, 1997.Traditional knowledge threatens environmental assessment. Policy Options, 17(9):34–36.Stevenson, M.G., 1997. Ignorance and prejudice threaten environmental assessment. Policy Options, 18(2):25–28.
  14. ↑ e.g., Berkes, F., 1999. Sacred Ecology:Traditional Ecological Knowledge and Resource Management.Taylor and Francis, xvi + 209pp.Huntington, H.P., 2000. Using traditional ecological knowledge in science: methods and applications. Ecological Applications, 10(5):1270–1274.Johannes, R.E., 1981.Words of the Lagoon: Fishing and Marine Lore in the Palau District of Micronesia. University of California Press, xiv + 245pp.
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